Finger vein recognition system and method

Abstract

The present invention discloses a finger vein recognition system comprising an image catching module, an image preprocess module, a feature points calculating module, a feature database, a first comparing module and a second comparing module. The feature points calculating module is connected to the image preprocess module for calculating a set of distances among a plurality of feature points. The first comparing module is connected to the feature points calculating module and the feature database for comparing the set of distances and generating a compared result of feature points. The second comparing module is connected to the image preprocess module, the feature database and the first comparing module for catching a set of vein shape and comparing the set of vein shape with the feature database for generating a compared result of shape similarity. Wherein, the second comparing module combines the compared result of feature points and the compared result of shape similarity for generating a recognized result of the finger vein.

What is claimed is: 
     
         1 . A finger vein recognition method, comprising:
 (S 1 ) catching a finger vein image;   (S 2 ) preprocessing the finger vein image;   (S 3 ) catching a plurality of feature points from the preprocessed finger vein image, and calculating a set of distances among the plurality of feature points;   (S 4 ) processing a first comparison for the set of distances with a feature database, and generating a compared result of feature point distances;   (S 5 ) catching a set of vein shape from the preprocessed finger vein image, processing a second comparison for the set of vein shape with the feature database, generating a compared result of shape similarity, combining the compared result of feature point distances and the compared result of shape similarity, and generating a recognized result of the finger vein.   
     
     
         2 . The finger vein recognition method of  claim 1 , wherein (S 2 ) further comprises:
 (S 21 ) processing the finger vein image for a Gaussian Smoothing;   (S 22 ) processing the finger vein image processed by the Gaussian Smoothing for a Convolution;   (S 23 ) processing the finger vein image processed by the Convolution for a Histogram Equalization;   (S 24 ) processing the finger vein image processed by the Histogram Equalization for a Binarization process; and   (S 25 ) processing the finger vein image processed by the Binarization process for a thinning process.   
     
     
         3 . The finger vein recognition method of  claim 2 , wherein (S 3 ) is used to catch the plurality of feature points from the finger vein image processed by the thinning process, and calculates the set of distances among the plurality of feature points. 
     
     
         4 . The finger vein recognition method of  claim 3 , wherein the plurality of feature points of (S 3 ) can be a plurality of branch points or edge points of the finger vein image processed by the thinning process. 
     
     
         5 . The finger vein recognition method of  claim 2 , wherein the set of vein shape of (S 5 ) processes the second comparison and generates a compared result of shape similarity by subtracted the finger vein image processed by the Binarization process from the finger vein image processed by the thinning process. 
     
     
         6 . A finger vein recognition system, comprising:
 a image catching module for catching a finger vein image;   a image preprocess module, connected to the image catching module, for preprocessing the finger vein image in accordance with a predetermined procedure;   a feature points calculating module, connected to the image preprocess module, for catching a plurality of feature points from the preprocessed finger vein image, and calculating a set of distances among the plurality of feature points;   a feature database for pre-storing a set of feature data;   a first comparing module, connected to the feature points calculating module and the feature database, for comparing the set of distances and generating a compared result of feature point distances; and   a second comparing module, connected to the image preprocess module, the feature database and the first comparing module, for catching a set of vein shape and comparing the set of vein shape with the feature database for generating a compared result of shape similarity;   
       wherein the second comparing module combines the compared result of feature point distances and the compared result of shape similarity for generating a recognized result of the finger vein. 
     
     
         7 . The finger vein recognition system of  claim 6 , wherein the predetermined procedure comprises:
 (S 21 ) processing the finger vein image for a Gaussian Smoothing;   (S 22 ) processing the finger vein image processed by the Gaussian Smoothing for a Convolution;   (S 23 ) processing the finger vein image processed by the Convolution for a Histogram Equalization;   (S 24 ) processing the finger vein image processed by the Histogram Equalization for a Binarization process; and   (S 25 ) processing the finger vein image processed by the Binarization process for a thinning process.   
     
     
         8 . The finger vein recognition system of  claim 7 , wherein the feature points calculating module catches the plurality of feature points from the finger vein image processed by the thinning process, and calculates the set of distances among the plurality of feature points. 
     
     
         9 . The finger vein recognition system of  claim 7 , wherein the set of vein shape generates a compared result of shape similarity by subtracted the finger vein image processed by the Binarization process from the finger vein image processed by the thinning process. 
     
     
         10 . The finger vein recognition system of  claim 8 , wherein the plurality of feature points can be a plurality of branch points or edge points of the finger vein image processed by the thinning process.